1. Introduction to Statistics / Core, Chapter 1 / i.) statistical data definitions
ii.) data measurement
iii.) discrete & continuous data
iv.) using & abusing statistics
v.) experiment design
vi.) sampling / Pg. 26
Ex. 1, 2, 3, 4, 5, 6 / 1.understand the basics of statistics
2.how to use statistics
3.elements of designing an experiment
4.types of sampling2
2. Describing, Exploring and Comparing Data
2-1, 2-2, 2-3, 2-4 / Core, Chapter 2 / i.) summarizing data
ii.) frequency tables
iii.) picturing data (presentation)
iv.) measures of center(mean, median, mode)
v.) skew / Pg. 40 - 41
Ex. 1, 2, 5, 6, 9, 10, 13, 15
Pg. 51 – 54
Ex. 1, 2, 3, 4, 6, 10, 14, 16, 19, 20, 23
Pg. 65 – 68
Ex. 1, 3, 5, 7, 10, 14 / 1. identify and draw a frequency table
2. understandingrelative &cumulative frequency
3. data presentationusing graphs, charts & tables
4. mean, median, mode
5. identify skewed data
3. Describing, Exploring and Comparing Data
2-5, 2-6, 2-7 / Core, Chapter 2 / i.) measures of center
ii.) measures of variance(sample & population)
iii.) measures of position
iv.) exploratory data analysis / Pg. 81 – 84
Ex. 2, 3, 7, 10, 14, 19, 22, 24
Pg. 91 – 94
Ex. 1, 2, 7, 10, 14, 17, 19, 21,
Pg. 102 – 103
Ex. 2, 7 / 1. understand variation of data
2. range and midrange of data
3. calculate std. deviation
4. z-scores and distribution
5. exploring and comparing data
4. Probability
3-1, 3-2, 3-3,
3-4 / Core, Chapter 3 / i.) basic probability
ii.) addition rule
iii.) multiplication rule basics / Pg. 123 – 127
Ex. 5, 6, 11, 18, 25, 28
Pg. 132 – 135
Ex. 1, 4, 11, 13, 19
Pg. 140 – 144
Ex. 1, 3, 7, 13, 15, 19, 21, 22 / 1. understand the law of large numbers
2. kinds of probability events
3. adding probabilities : compound event, mutually exclusive
4. multiplying probabilities
5. understand conditional events
6. know the difference between independent and dependent events
5. Probability
3-5, 3-6, 3-7 / Core, Chapter 3 / i.) multiplication rule complements and conditional
ii.) counting with factorial, permutations and combinations / Pg. 149 – 151
Ex. 1, 3, 5, 7, 13
Pg. 164 – 168
Ex. 1, 2, 3, 6, 11, 14, 20, 25 / 1. adding probabilities : compound event, mutually exclusive
2. multiplying probabilities
3. understand conditional events
4. know the difference between independent and dependent events
6. Probability Distribution:
Binomial Distribution
4-1, 4-2, 4-3, 4-4, / Core, Chapter 4 / i.) random variables
ii.) binomial distribution
iii.) mean, var., std. dev for binomial dist.
iv.) poisson distribution
v.) mean, var., std. dev for poissondist. / Pg. 190 - 194
Ex. 1, 3, 5, 8, 10, 13, 17, 20
Pg. 201 - 205
Ex. 4, 5, 9, 12, 13, 17, 21, 23, 26, 28
Pg. 207 – 210
Ex. 1, 4, 5, 8, 11, 16
Pg. 213 – 215
Ex. 2, 4, 5, 9 / 1. understand the properties of a binomial distribution
2. know how to calculate expected value
3. how to use the binomial formula
4. how and when to us the poisson distribution
7. Probability Distribution:
Possion Distribution
4-4, 4-5 / Core, Chapter 4 / i.) binomial distribution
ii.) poisson distribution
iii.) mean, var., std. dev for poisson dist. / Pg. 238 – 246
Ex. 1, 4, 5, 9 / 1. understand the properties of a binomial distribution
2. know how to calculate expected value
3. how to use the binomial formula
4. understanding the properties of a poisson distribution
5. how and when to us the poisson distribution
8. Normal Probability Distribution
5-2, 5-3, 5-4 / Core, Chapter 5 / i.) standard normal dist.
ii.) normal dist:
finding prob.
iii.) normal dist:
finding values
iv.) sketching normal curves
v.) z-scores / Pg. 239-241
Ex. 2, 3, 5, 9, 13, 14, 19, 32,
Pg. 245-248
Ex. 1, 3, 6, 9, 15, 20
Pg. 252-255
Ex. 2, 5, 6, 10, 14, 18 / 1. what is a standard normal distribution
2. understand how to use z scores and find them
3. able to sketch normal curves
4. able to use a
z-score table
9. Normal Probability Distribution
5-5, 5-6, 5-7 / Core, Chapter 5 / i.) the central limit theorem
ii.) finite population corrections
iii.) normal dist as approx. to binomial dist.
iv.) continuity correction
v.) determining normality / Pg. 263-266
Ex. 2, 4, 8, 13,
Pg. 275-279
Ex. 1, 2, 10, 11, 16, 22 / 1. understand the central limit theorem
2. understand sampling distribution
3. approx binom. dist with normal dist.
4. how to use continuity correction
5.draw normal curve areas
Course Detail:
Descriptive Statistics gives students the basic principles and quantitative skills for applying descriptive statistics in life. Some understanding of mathematics will be needed but not at a high level. The course will use a combination of lectures, tutorials, group assignments/presentations, directed readings, and other media to educate the student.
The core text for the course will be Mario F. TriolaElementary Statistics8thedition. Additional readings and problems will be directed as required.
Evaluation Methods:
Tutorial (participation & quizzes) – 20%
Statistical Calculation Report – 20%
Exam – 60%
You are required to attend the weekly tutorials as ALL Quizzes and Exams will be given during the tutorial sessions. You will be given a set of questions and problems for each tutorial relevant to the chapters covered in class.
All Quizzes and Exams will require you to SHOW ALL of your work in arriving at your answer. I will give partial credit if you worked the problem correctly, but calculated an incorrect answer. If you do not show your work, you will get NO CREDIT for your answer.
Some questions will ask for your analysis. This will require you to write a short paragraph for your answer. I will grade you on the content, not the grammar, but if it is too difficult to understand, I will deduct points.
Exams will be 2 to 2½ hours.